Abstract
The robot and computer vision community has seen a lot of novelties developed in the past few years as a result of the appearance of cheap RGB-D sensors spearheaded by the Kinect sensor. In this paper, the feasibility of using an RGB-D camera in detecting, segmenting, reconstructing and measuring chronic wounds in 3D is explored. The wound is detected by implementing nearest-neighbor approach on color histograms generated from the image. The proposed wound segmentation procedure extracts the wound contour using visual and geometrical information of the surface. A procedure comparable to KinectFusion is used for the 3D reconstruction of the wound. In order to achieve real-time performance, the whole system is realized in CUDA. The resulting system provides an accurate colored 3D model of the segmented wound and enables the user to determine the volume, area and perimeter of the wound, thereby aiding in the selection of a suitable therapy. The developed system is experimentally evaluated using the Saymour II wound care model by VATA Inc.
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